Arabi, B., S. Munisamy, A. Emrouznejad and F. Shadman (2014), “Power Industry Restructuring and Eco-Efficiency Changes: A New Slacks-Based Model in Malmquist-Luenberger Index Measurement,” Energy Policy, 68: 132–145.

Arabi, B., S. Munisamy, A. Emrouznejad and F. Shadman (2014), “Power Industry Restructuring and Eco-Efficiency Changes: A New Slacks-Based Model in Malmquist-Luenberger Index Measurement,” Energy Policy, 68: 132–145.

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003–2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis.

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Ghasemi, M. R., J. Ignatius; A. Emrouznejad (2014) “A bi-objective weighted model for improving the discrimination power in MCDEA”, European Journal of Operational Research, 233 (3): 640–650.

Ghasemi, M. R., J. Ignatius; A. Emrouznejad (2014) “A bi-objective weighted model for improving the discrimination power in MCDEA”, European Journal of Operational Research, 233 (3): 640–650.

Lack of discrimination power and poor weight dispersion remain major contention issues in Data Envelopment Analysis (DEA) models, which have also hampered the developments in the multiobjective DEA domain. Since the initial multi- criteria DEA (MCDEA) model of Li and Reeves ( 1999), only one other research by Bal, Örkcü and Çelebio?lu ( 2010) attempted to solve the MCDEA framework through two goal programming approaches, i.e. GPDEA-CCR and GPDEA-BCC. It was claimed that both models improved upon the discrimination power of DEA by balancing the distribution of input-output weights. It was also claimed that both GPDEA models are major improvements to the original MCDEA of Li and Reeves (1999). In this research we first checked the validity of GPDEA models and found that they do not improve the discrimination power as it has been claimed, we further propose an alternative solution to the formulation using bi-objective linear programming. It is shown that the proposed bi-objective multiple criteria DEA(BiO-MCDEA) performs better than the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 26 European Union member countries is further used to describe the efficacy of our approach.

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Bahari A., A. Emrouznejad (2014) “Influential DMUs and outlier detection in Data Envelopment Analysis with an Application to Health Care”. Annals of Operations Research, 223 (1):95-108.

Bahari A., A. Emrouznejad (2014) “Influential DMUs and outlier detection in Data Envelopment Analysis with an Application to Health Care”. Annals of Operations Research, 223 (1):95-108.

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric Data Envelopment Analysis (DEA) models as developed by Yang et al. (2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection.

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Emrouznejad, A. (2014) “Advances in Data Envelopment Analysis”. Annals of Operations Research, 214 (1): 1-4.

Emrouznejad, A. (2014) “Advances in Data Envelopment Analysis”. Annals of Operations Research, 214 (1): 1-4.

Since its introduction in 1978, Data Envelopment Analysis (DEA) has become one of the preeminent non-parametric methods for measuring efficiency and productivity of decision making units. Charnes, Cooper, and Rhodes (1978) provided the original DEA constant returns to scale (CRS) model, later extended to variable returns to scale (VRS) by Banker Charnes, and Cooper (1984).  These ‘standard’ models are known by the acronyms CCR and BCC, respectively, and are now employed routinely in areas that range from assessment of public sectors, such as hospitals and health care systems, schools, and universities, to private sectors such as banks and financial institutions (Emrouznejad, et al, 2008, 2011). The main objective of this volume is to publish original studies that are beyond the two standard CCR and BCC models with both theoretical and practical applications using advanced models in Data Envelopment Analysis.

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Hatami-Marbini, A., A. Emrouznejad, P. J. Agrell (2014) Interval data without sign restrictions in DEA, Applied Mathematical Modelling, 38: 2028–2036.

Hatami-Marbini, A., A. Emrouznejad, P. J. Agrell (2014) Interval data without sign restrictions in DEA, Applied Mathematical Modelling, 38: 2028–2036.

Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches.

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Banker R., A., Emrouznejad, F. Vargas, P. Flores (2014), Sustainable Development and Performance Measurement: Proceedings of the International DEA Workshop, September 17-19, 2014, Hermosillo, Sonora, Mexico, ISBN: 978 1 85449 482 5.

Banker R., A., Emrouznejad, F. Vargas, P. Flores (2014), Sustainable Development and Performance Measurement: Proceedings of the International DEA Workshop, September 17-19, 2014, Hermosillo, Sonora, Mexico, ISBN: 978 1 85449 482 5.

Title: Sustainable Development and Performance Measurement

Subtitle (series): Proceedings of the International DEA Workshop

Venue: September 17-19, 2014, Hermosillo, Sonora, Mexico

Edited by: Rajiv Banker, Ali Emrouznejad, Francisco Vargas and Pedro Flores

Date of Publication: November 2014

Number of Page: 100pp

ISBN: 978 1 85449 482 5

DOI: 10.13140/RG.2.1.1387.2169

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Emrouznejad, A., R. Banker, S. Munisamy, B. Arabi (2014), Theory and Applications of Data Envelopment Analysis, Proceedings of the 12th International Conference of DEA, April 2014, University of Malaya, Kuala Lumpur, Malaysia, ISBN: 978 1 85449 487 0.

Emrouznejad, A.,  R. Banker, S. Munisamy, B. Arabi (2014), Theory and Applications of Data Envelopment Analysis,  Proceedings of the 12th International Conference of DEA, April 2014, University of Malaya, Kuala Lumpur, Malaysia, ISBN: 978 1 85449 487 0.

Title: Recent Developments in Data Envelopment Analysis and its Applications

Subtitle (series): Proceedings of the 12th International Conference on Data Envelopment Analysis

Venue: DEA2014, April 2014, Kuala Lumpur, Malaysia

Edited by: Ali Emrouznejad, Rajiv Banker, Susila M. Doraisamy and Behrouz Arabi

Date of Publication: November 2014

Number of Page: 416pp

ISBN: 978 1 85449 487 0

DOI: 10.13140/RG.2.1.1649.3608

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Banker R., A. Emrouznejad, H. Bal, I. Alp, M. Ali Cengiz (2013), Data Envelopment Analysis and Performance Measurement, Proce

Banker R., A. Emrouznejad,  H. Bal, I. Alp, M. Ali Cengiz (2013), Data Envelopment Analysis and Performance Measurement,  Proceedings of the 11th International Conference of DEA, June 2013, Samsun, Turkey, ISBN: 978 1 85449 477 1.

Title: Data Envelopment Analysis and Performance Measurement

Subtitle (series): Proceedings of the 11th International Conference on Data Envelopment Analysis

Venue: DEA2013, June 2013, Samsun, Turkey

Edited by: Rajiv Banker, Ali Emrouznejad, Hasan Bal, Ihsan Alp, Mehmet Ali Cengiz

Date: April 2014

Number of Page: 424pp

ISBN: 978 1 85449 477 1

DOI: 10.13140/RG.2.1.3353.2966

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Emrouznejad, A. and E. Cabanda (2014). Managing Service Productivity: Uses of Frontier Efficiency Methodologies and MCDM for Improving Service Performance. In the series of “International Series in Operations Research & Management Science”, Springer-Verlag, ISBN 978-3-662-43436-9.

Emrouznejad, A. and E. Cabanda (2014). Managing Service Productivity: Uses of Frontier Efficiency Methodologies and MCDM for Improving Service Performance. In the series of “International Series in Operations Research & Management Science”, Springer-Verlag, ISBN 978-3-662-43436-9.

The main objective of this book is to provide the necessary background to work with existing DEA models. Once the material in this book has been mastered, the reader will be able to apply DEA models to his or her problems for measuring comparative efficiency of decision-making units in any service industry.

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Emrouznejad, A. and M. Tavana (2014). Performance Measurement with Fuzzy Data Envelopment Analysis. In the series of “Studies in Fuzziness and Soft Computing”, Springer-Verlag, ISBN 978-3-642-41371-1.

Emrouznejad, A. and M. Tavana (2014). Performance Measurement with Fuzzy Data Envelopment Analysis. In the series of “Studies in Fuzziness and Soft Computing”, Springer-Verlag, ISBN 978-3-642-41371-1.

Since its introduction in 1978, Data Envelopment Analysis (DEA) has become one of the preeminent non-parametric methods for measuring efficiency and productivity of decision making units. DEA models are now employed routinely in areas that range from assessment of public sectors such as hospitals and healthcare systems, schools and universities to private sectors such as banks and financial institutions. The advantage of DEA is to accommodate multiple inputs and multiple outputs for measuring the relative efficiencies of a set of homogeneous decision making units (DMUs).
One limitation of the conventional DEA models is that they can only handle crisp input and output data. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. The aim of this book is to study various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This monograph is the first in fuzzy DEA (FDEA). It contains both the authors’ research work on fuzzy DEA and other developments, especially in the last 10 years, and it is a good indication of the outgrowth of the field of fuzzy data envelopment analysis.
With the exception of some basic notions in DEA and fuzzy theory, the book is completely self-contained. Important concepts in fuzziness and measuring efficiency are carefully motivated and introduced. Specifically, we have excluded any technical material that does not contribute directly to the understanding of fuzzy or DEA. Many other excellent textbooks are available today that discuss DEA in much more technical detail than is provided here. This book is aimed at upperlevel undergraduate as well as beginning graduate students who want to learn more about fuzziness in DEA or who are pursuing research in fuzzy DEA and related areas.
The main objective of this book is to provide the necessary background to work with existing fuzzy DEA models. Once the material in this book has been mastered, the reader will be able to apply fuzzy DEA models to his or her problems for measuring comparative efficiency of decision making units with imprecise data.

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